When a woman walks, the muscles in her leg contract in proper succession to take a step. The woman does not concentrate on the order and timing of muscle concentration; the process is automatic. But something must plan and execute each step; something must establish the pattern of muscle contraction necessary for locomotion. That "something" is a central pattern generator (CPG). A CPG is a neural circuit that drives a set of muscles to perform a motor task. A CPG not only initiates a series of muscle contractions; it also coordinates the timing and phasing between the different muscles performing the task. The output of a CPG is continuously reconfigured because the task changes in response to the circumstances. For example, the woman may switch from a walk to a run when she sees her train leaving the station without her. Clearly, the output of a CPG must be rhythmic and faithful, yet highly modulatable. To understand how a dynamic system meets these opposing needs, we study a very small CPG containing only 14 neurons. The pyloric CPG mediates the continuous, rhythmic contractions of the Crustacean foregut. Because the muscles surrounding the Crustacean foregut are striated, not smooth; and because the foregut is chitinized and derived from ectoderm, not endoderm; the foregut is more similar to an external locomotory appendage than a vertebrate gastro-intestinal tract. Thus, the pyloric CPG is a model system for motor behaviors like locomotion, not digestion. The 14 neurons of the pyloric network fall into six types. Each pyloric cell type possessing a unique modulatable transient potassium current, or A-current (Ia), that is instrumental transient potassium current, or A- current (IA), that is instrumental in determining the over-changing outputs of this network. The baseline differences between the six pyloric IAS, and their functional correlates, are very well defined. Thus, we can use these six IAs as a simple model to study how the network maintains phenotypically distinct, yet dynamic components. Surprisingly, we discovered that although the IA is distinct in every cell type, the same gene encodes the A-channel alpha-subunits in all pyloric cells. Quantitative differences in the level of sha1 gene expression account for differences in A-channel density between cells, but they cannot account for differences in biophysical properties of the various pyloric IAS. One mechanisms that could account for IA variation is cell-specific post- 0translational modifications of the sha1 channel. We propose to explore the role of channel phosphorylation in creating baseline and neuromodulatory differences in pyloric IAS. Using mutational analysis of the sha1 gene expressed in an STG organ culture system, we will examine the phosphorylation sites involved in regulating the pyloric IAS, and which sites are utilized in different cells under different conditions. The data resulting from this grant will help to elucidate the molecular mechanisms underlying the adaptive nature of dynamic networks.